Data and analytics are at the center of today’s student success movement. Increased interest and access to institutional data are helping colleges and universities identify systematic and structural barriers to retention and graduation. Predictive analytics is making proactive advising possible at scale.

This study aims at providing explanations of students’ behaviors on LMS by incorporating dispositional dimensions (e.g., self-regulation and emotions) into conventional learning analytics models. Using a combination of demographic, trace, and self-reported data.

Not all learning analytics are the same. Discover how proactive learning analytics help you influence and improve ongoing learning processes by predicting the future and creating recommendations for action. Identify the 4 key elements that will determine the success of your analytics journey.